Interaction Effects in the Sexual Spread of HIV/AIDS

Sara Hertog, University of Wisconsin at Madison

As HIV continues to exact its toll on populations around the world, improved understanding of the factors that operate to produce or suppress epidemics remains crucial. This paper employs a biobehavioral macrosimulation model to assess the interaction effect between two of the most critical behavioral determinants of the sexual spread of HIV: the rates of sexual partner change and patterns of sexual mixing between population subgroups. Results simulated under two rates of partner change scenarios and under various degrees of assortativeness in sexual mixing patterns reveal that when the rate of partner change is high, greater assortativeness tends to decrease the ultimate size of the epidemic, but the opposite relationship is shown in simulations with relatively low rates of partner change. This interaction effect, which further depends on underlying HIV transmission probabilities, is consequential for the size and shape of the epidemic curve and identification of high-risk population subgroups.